Difference between revisions of "2009:Audio Music Similarity and Retrieval Results"
| Line 40: | Line 40: | ||
<csv p=3>ams/evalutron/summary_evalutron.csv</csv> | <csv p=3>ams/evalutron/summary_evalutron.csv</csv> | ||
| − | ===Friedman Test | + | ===Friedman's Test (FINE Scores)=== |
| − | The Friedman test was run in MATLAB against the Fine summary data over the 100 queries.<br /> | + | The Friedman test was run in MATLAB against the '''Fine''' summary data over the 100 queries.<br /> |
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | ||
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evalutron.fine.friedman.tukeyKramerHSD.csv | evalutron.fine.friedman.tukeyKramerHSD.csv | ||
| − | [ | + | |
| + | ===Friedman's Test (BROAD Scores)=== | ||
| + | The Friedman test was run in MATLAB against the '''BROAD''' summary data over the 100 queries.<br /> | ||
| + | Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05); | ||
| + | |||
| + | <csv p=3>ams/evalutron/evalutron.cat.friedman.tukeyKramerHSD.csv</csv> | ||
| + | |||
| + | https://music-ir.org/mirex/2009/results/ams/evalutron/small.evalutron.cat.friedman.tukeyKramerHSD.png | ||
| + | |||
===Summary Results by Query=== | ===Summary Results by Query=== | ||
These are the mean FINE scores per query assigned by Evalutron graders. The FINE scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0.0 and 10.0. A perfect score would be 10. Genre labels have been included for reference. | These are the mean FINE scores per query assigned by Evalutron graders. The FINE scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0.0 and 10.0. A perfect score would be 10. Genre labels have been included for reference. | ||
| − | <csv> | + | <csv p=3>ams/evalutron/fine_scores.csv</csv> |
These are the mean BROAD scores per query assigned by Evalutron graders. The BROAD scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 (not similar) and 2 (very similar). A perfect score would be 2. Genre labels have been included for reference. | These are the mean BROAD scores per query assigned by Evalutron graders. The BROAD scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 (not similar) and 2 (very similar). A perfect score would be 2. Genre labels have been included for reference. | ||
| − | <csv> | + | |
| + | <csv p=3>ams/evalutron/cat_scores.csv</csv> | ||
===Anonymized Metadata=== | ===Anonymized Metadata=== | ||
Revision as of 14:46, 14 October 2009
Contents
Introduction
General Legend
Team ID
ANO = Anonymous
BF = Benjamin Fields
BSWH = Dmitry Bogdanov, Joan Serrà, Nicolas Wack, and Perfecto Herrera
CL1 = Chuan Cao, Ming Li
CL2 = Chuan Cao, Ming Li
GT = George Tzanetakis
LR = Thomas Lidy,Andreas Rauber
ME = Franc┬╕ois Maillet,Douglas Eck
PS1 = Tim Pohle1, Dominik Schnitzer1
PS2 = Tim Pohle1, Dominik Schnitzer1
SH = Stephan H├╝bler
Broad Categories
NS = Not Similar
SS = Somewhat Similar
VS = Very Similar
Calculating Summary Measures
Fine(1) = Sum of fine-grained human similarity decisions (0-10).
PSum(1) = Sum of human broad similarity decisions: NS=0, SS=1, VS=2.
WCsum(1) = 'World Cup' scoring: NS=0, SS=1, VS=3 (rewards Very Similar).
SDsum(1) = 'Stephen Downie' scoring: NS=0, SS=1, VS=4 (strongly rewards Very Similar).
Greater0(1) = NS=0, SS=1, VS=1 (binary relevance judgement).
Greater1(1) = NS=0, SS=0, VS=1 (binary relevance judgement using only Very Similar).
(1)Normalized to the range 0 to 1.
Overall Summary Results
NB: The results for BK2 were interpolated from partial data due to a runtime error.
file /nema-raid/www/mirex/results/ams/evalutron/summary_evalutron.csv not found
Friedman's Test (FINE Scores)
The Friedman test was run in MATLAB against the Fine summary data over the 100 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
file /nema-raid/www/mirex/results/ams/evalutron/evalutron.fine.friedman.tukeyKramerHSD.csv not found
evalutron.fine.friedman.tukeyKramerHSD.csv
Friedman's Test (BROAD Scores)
The Friedman test was run in MATLAB against the BROAD summary data over the 100 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
file /nema-raid/www/mirex/results/ams/evalutron/evalutron.cat.friedman.tukeyKramerHSD.csv not found
Summary Results by Query
These are the mean FINE scores per query assigned by Evalutron graders. The FINE scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0.0 and 10.0. A perfect score would be 10. Genre labels have been included for reference.
file /nema-raid/www/mirex/results/ams/evalutron/fine_scores.csv not found
These are the mean BROAD scores per query assigned by Evalutron graders. The BROAD scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 (not similar) and 2 (very similar). A perfect score would be 2. Genre labels have been included for reference.
file /nema-raid/www/mirex/results/ams/evalutron/cat_scores.csv not found
Anonymized Metadata
Raw Scores
The raw data derived from the Evalutron 6000 human evaluations are located on the Audio Music Similarity and Retrieval Raw Data page.
